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Real-World Problems Through Computational Thinking Tools and Concepts: the Case of Coronavirus 46 Disease (COVID-19) The current issue and full text archive of this journal is available on Emerald Insight at: https://www.emerald.com/insight/2397-7604.htm JRIT 14,1 Real-world problems through computational thinking tools and concepts: the case of coronavirus 46 disease (COVID-19) Received 2 December 2020 Hatice Beyza Sezer and Immaculate Kizito Namukasa Revised 6 January 2021 Accepted 6 January 2021 Department of Curriculum Studies, Western University Faculty of Education, London, Canada Abstract Purpose – Many mathematical models have been shared to communicate about the COVID-19 outbreak; however, they require advanced mathematical skills. The main purpose of this study is to investigate in which way computational thinking (CT) tools and concepts are helpful to better understand the outbreak, and how the context of disease could be used as a real-world context to promote elementary and middle-grade students’ mathematical and computational knowledge and skills. Design/methodology/approach – In this study, the authors used a qualitative research design, specifically content analysis, and analyzed two simulations of basic SIR models designed in a Scratch. The authors examine the extent to which they help with the understanding of the parameters, rates and the effect of variations in control measures in the mathematical models. Findings – This paper investigated the four dimensions of sample simulations: initialization, movements, transmission, recovery process and their connections to school mathematical and computational concepts. Research limitations/implications – A major limitation is that this study took place during the pandemic and the authors could not collect empirical data. Practical implications – Teaching mathematical modeling and computer programming is enhanced by elaborating in a specific context. This may serve as a springboard for encouraging students to engage in real- world problems and to promote using their knowledge and skills in making well-informed decisions in future crises. Originality/value – This research not only sheds light on the way of helping students respond to the challenges of the outbreak but also explores the opportunities it offers to motivate students by showing the value and relevance of CT and mathematics (Albrecht and Karabenick, 2018). Keywords CT, Programming languages, SIR model, COVID-19 Paper type Research paper © Hatice Beyza Sezer and Immaculate Kizito Namukasa. Published in Journal of Research in Innovative Teaching & Learning. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http:// creativecommons.org/licences/by/4.0/legalcode Funding: This work was funded by the Teaching Fellowship of Dr. Namukasa ([email protected]) on Maker Education at the Center of Teaching and Learning, Western University. Availability of data and material: Links to the website apps which are the sources of our data are Journal of Research in Innovative provided. Teaching & Learning Code availability: Links to the code for the simulations shown in this manuscript are provided in the Vol. 14 No. 1, 2021 pp. 46-64 main text. Emerald Publishing Limited Authors’ contributions: All authors contributed equally to this work. 2397-7604 DOI 10.1108/JRIT-12-2020-0085 Conflicts of interest/Competing interests: The authors have no conflict of interest. Introduction Understanding When the novel coronavirus was first identified, countries and the World Health Organization real-world (WHO) could not largely understand the risk and rate at which this disease would culminate into a global crisis. The following questions needed to be answered rapidly by experts when problems responding to the outbreak: at what rate was the infection going to spread in different through CT populations? How were experts, health officials and policymakers going to effectively convey information that would help in understanding the nature of the outbreak? How were they to demonstrate how the different recommended collective control protocols would alter the 47 spread of the outbreak? As Shepherd (2020) indicates, it became very crucial to make the public comprehend the severity of the health risks of this novel virus and the need to critically interpret and implement the precautions recommended by the public authorities. Mathematics, along with other disciplines, is essential in helping to understand several aspects of an outbreak. For instance, health officials and policymakers may communicate about the rates, trends and parameters of the outbreak. Kucharski (2020) mentions that mathematics can also help with determining what needs to be done to help control the rates of morbidity and mortality. By providing tools for assessment, analysis and predictions, mathematical modeling has been very vital in efforts by experts from a variety of fields who have investigated the dynamics of both emerging and reemerging infectious diseases and insights drawn from them help policymakers to determine and debate courses of action that may prevent high mortality rates (Siettos and Russo, 2013; Wang et al., 2020; Yates, 2020). Many models are about the risks associated with a pandemic, the probability and rate of spread in a population and the effects of possible interventions to reduce morbidity and mortality (Rodrigues, 2016; Walters et al., 2018). Those mathematical models, however, use sophisticated mathematics that is normally only understood by experts in fields that make or use mathematics. Complex mathematics equations, data displays and graphs make it difficult to comprehend the data and the dynamics behind these mathematics artefacts for nonexperts. Computational and programming tools used to compute the equations or illustrate the visualizations are equally complex, as they require understanding of the tools and languages used; however, interactive illustrations of the mathematical models of outbreak, which utilized recent and less sophisticated tools for computational programming such as block-based and text-based programming languages, make it easy for the mathematical models of outbreak to be read and understood by the public (Froese, 2020; Resnick, 2020; Yeghikyan, 2020). Many of these models are designed to afford opportunities to experiment with different scenarios, and users may view, study and modify the code for the simulations. Recent school activities also show that students might be able to better understand real-world problems by using programming languages. The principal of the Oklahoma School of Science and Math, Dr. Frank Wang, for instance, claimed that offering students chances to play with the tools including the mathematical models, similar to those that real epidemiologists were using, enabled students to acquire a better idea of the pandemic on their own (Skarky, 2020). In this research paper, we focus on computational simulations of outbreak based on susceptible – infectious – recovered (SIR) model which commonly have been used to illustrate the spread of the COVID-19 disease (Ciarochi, 2020). We selected and analyzed two sample simulations of the SIR model designed using a block-based programming language, Scratch. These simulations, in addition to being dynamic and interactive, have visible code hence they are modifiable, which helps students who wish to experiment with them. We specifically investigated: (1) the ways in which Scratch simulations were accessible by students to comprehend the dynamics of the outbreaks and the response needed to slow down the rate of the outbreak and (2) the extent to which these simple simulations illustrate the impacts of variations in precautions and policies implemented during pandemic crisis, including social/ physical distancing, reduced mobility (through staying at home, isolation or quarantine) JRIT and regular hand washing. Generally, this study aims to shed light on opportunities of using 14,1 CT tools during the current global health crisis. Literature review Computational thinking and its integration with real-world problems The term CT was coined by Papert (1980) and popularized by Wing (2014) as “the thought 48 processes involved in formulating a problem and expressing its solution(s) in such a way that a computer–human or machine – can effectively carry [it] out” (Wing, 2017, p. 8). Hoyles et al. (2002) and Wilkerson-Jerde (2014) designed environments of computational programming coupled with computational modeling of mathematics and science concepts, processes and systems, for example, population dynamics (e.g. Stroup and Wilensky, 2014; Wilkerson-Jerde et al., 2015a, b). While focusing on CT, these researchers engaged students in the practices of mathematicians (Wilkerson-Jerde, 2014) and of STEM professionals (Wilkerson-Jerde et al., 2018). Haduong (2019) maintains that the increasing relationship between power and technology in today’s world makes it even more essential to use digital tools to examine children’s and youth’s experiences, goals and expectations which influence both their current and future lives. To Skovsmose (1994) the role mathematics plays in technological development shows its formatting power on society and shows the potential role of mathematics in helping to positively shape the society. The reality is, however, given the way mathematics
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